Independent Research at the
Intersection of AI and Finance
DAI (DStrategyTech AI) publishes practitioner-led analysis, briefings, and benchmarks across three research domains — designed to help financial leaders, risk professionals, and technology operators make better decisions about AI.
Financial Risk
AI is changing how institutions model and respond to risk — and introducing new categories of risk in the process.
Topics include
- AI model risk and governance
- Fraud detection and prevention
- Deepfake financial fraud
- Identity risk in digital banking
- Regulatory compliance: OCC, CFPB, FFIEC, SEC
Financial Operations
AI is automating financial workflows faster than most organizations are prepared for. We research what responsible adoption looks like in practice.
Topics include
- AI-driven automation in finance functions
- Cost management and optimization
- AI in audit and internal controls
- Process intelligence and workflow analysis
- Operational risk from agentic AI in finance
Prediction Markets & Forecasting
Forecasting is getting faster, more granular, and increasingly AI-driven. We research the accuracy, adoption, and strategic use of these tools.
Topics include
- AI economic forecasting models
- Prediction market accuracy and adoption
- Real-time risk signal analysis
- Scenario modeling for financial institutions
- LLM applications in financial forecasting
Practitioner-Led. Openly Accessible. Honest About Uncertainty.
DAI was built on a simple conviction: the most important research on AI and financial services should not be gatekept. It should be grounded in real-world practice, independent of vendor relationships, and free to read. Every briefing, benchmark, and analysis we publish is evaluated against one question — does this help someone make a better decision?